Cloud infrastructure of INP'S Astana branch - PE "NULITS" and its integration with distributed JINR cloud infrastructure

The article describes the Institute of Nuclear Physics’ (INP) Astana branch - private establishments “Nazarbayev University Library and IT services” (PE NULITS) cloud and its integration with the distributed cloud infrastructure consisting of the Laboratory of Information Technologies of the Joint Institute for Nuclear Research (JINR) cloud as well as clouds of some JINR Member State organizations. It explains a motivation of that work, an approach it is based on, working plan of the integration

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve

Detection of the Diffuse Supernova Neutrino Background with JUNO

As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

CERN Tape Archive Workshop : CTA 2024

This presentation summarizes the current state of tape storage systems at the Joint Institute for Nuclear Research (JINR) and gives our current vision of its future in response to the discontinuation of Enstore support. We provide a brief description of two of our currently operating tape systems: a 90 PB instance built on dCache/Enstore and an 11 PB instance based by EOS/CTA. Additionally, we share initial insights gained from operating the EOS/CTA system

Evolution and Perspectives of the Service for Parallel Applications Running at JINR Multifunctional Information and Computing Complex

Nowadays scientists use cloud computing as a routine tool in a lot of fields of their research. Various Multifunctional Information and Computing Complex (MICC) resources are provided for JINR users to perform a wide range of scientific computations. The JINR cloud service for parallel applications was developed in order to simplify scientists’ work on running similar tasks but on different MICC resources and also to speed up the process of reaching significant results. There are several components with a flexible and modular architecture that allow running a various number of applications using different types of computational resources. The service is constantly developing and improving with the help of the users’ feedback. Some changes in web-interface were made to improve users’ experience: there was added the possibility to choose a certain type of particular application, to set a description for a job, to run multiple tasks, to notify a user about successful job submission and its completion. Moreover, accessibility of job results was reworked: when the job is done, its output is uploaded at the external file storage, where it becomes available at the auto-generated unique URL for downloading by the user and further analysis and/or visualization

Evolution and Perspectives of the Service for Parallel Applications Running at JINR Multifunctional Information and Computing Complex

Nowadays scientists use cloud computing as a routine tool in a lot of fields of their research. Various Multifunctional Information and Computing Complex (MICC) resources are provided for JINR users to perform a wide range of scientific computations. The JINR cloud service for parallel applications was developed in order to simplify scientists’ work on running similar tasks but on different MICC resources and also to speed up the process of reaching significant results. There are several components with a flexible and modular architecture that allow running a various number of applications using different types of computational resources. The service is constantly developing and improving with the help of the users’ feedback. Some changes in web-interface were made to improve users’ experience: there was added the possibility to choose a certain type of particular application, to set a description for a job, to run multiple tasks, to notify a user about successful job submission and its completion. Moreover, accessibility of job results was reworked: when the job is done, its output is uploaded at the external file storage, where it becomes available at the auto-generated unique URL for downloading by the user and further analysis and/or visualization

Integrated cloud infrastructure of the LIT JINR, PE “NULITS” and INP's Astana branch

The article describes the distributed cloud infrastructure deployed on the basis of the resources of the Laboratory of Information Technologies of the Joint Institute for Nuclear Research (LIT JINR) and some JINR Member State organizations. It explains a motivation of that work, an approach it is based on, lists of its participants among which there are private entity “Nazarbayev University Library and IT services” (PE “NULITS”) Autonomous Education Organization “Nazarbayev University” (AO NU) and The Institute of Nuclear Physics’ (INP's) Astana branch

Integrated cloud infrastructure of the LIT JINR, PE “NULITS” and INP's Astana branch

The article describes the distributed cloud infrastructure deployed on the basis of the resources of the Laboratory of Information Technologies of the Joint Institute for Nuclear Research (LIT JINR) and some JINR Member State organizations. It explains a motivation of that work, an approach it is based on, lists of its participants among which there are private entity “Nazarbayev University Library and IT services” (PE “NULITS”) Autonomous Education Organization “Nazarbayev University” (AO NU) and The Institute of Nuclear Physics’ (INP's) Astana branch

JINR CLOUD SERVICE FOR SCIENTIFIC AND ENGINEERING COMPUTATIONS

Pretty often small research scientific groups do not have access to powerful enough computational resources required for their research work to be productive. Global computational infrastructures used by large scientific collaborations can be challenging for small research teams because of bureaucracy overhead as well as usage complexity of underlying tools. Some researchers buy a set of powerful servers to cover their own needs in computational resources. A drawback of such approach is a necessity to take care about proper hosting environment for these hardware and maintenance which requires a certain level of expertise. Moreover a lot of time such resources may be underutilized because а researcher needs to spend a certain amount of time to prepare computations and to analyze results as well as he doesn’t always need all resources of modern multi-core CPUs servers. The JINR cloud team developed a service which provides an access for scientists of small research groups from JINR and its Member State organizations to computational resources via problem-oriented (i.e. application-specific) web-interface. It allows a scientist to focus on his research domain by interacting with the service in a convenient way via browser and abstracting away from underlying infrastructure as well as its maintenance. A user just sets a required values for his job via web-interface and specify a location for uploading a result. The computational workloads are done on the virtual machines deployed in the JINR cloud infrastructure